The concepts of programmable switches and software-defined networking (SDN) give developers flexible and deep control over the behavior of switches. We expect these concepts to dramatically improve the functionality of switches. In this paper, we focus on the concept of Deeply Programmable Networks (DPN), where data planes are programmable, and application switches based on DPN. We then propose a method to improve the performance of a key-value store (KVS) through an application switch. First, we explain the DPN and application switches. The DPN is a network that makes not only control planes but also data planes programmable. An application switch is a switch that implements some functions of network applications, such as database management system (DBMS). Second, we propose a method to improve the performance of Cassandra, one of the most popular key-value based DBMS, by implementing a caching function in a switch in a dedicated network such as a data center. The proposed method is expected to be effective even though it is a simple and traditional way because it is in the data path and the center of the network application. Third, we implement a switch with the caching function, which monitors the accessed data described in packets (Ethernet frames) and dynamically replaces the cached data in the switch, and then show that the proposed caching switch can significantly improve the KVS transaction performance with this implementation. In the case of our evaluation, our method improved the KVS transaction throughput by up to 47%.

In order to erase data including confidential information stored in storage devices, an unrelated and random sequence is usually overwritten, which prevents the data from being restored. The problem of minimizing the cost for information erasure when the amount of information leakage of the confidential information should be less than or equal to a constant asymptotically has been introduced by T. Matsuta and T. Uyematsu. Whereas the minimum cost for overwriting has been given for general sources, a single-letter characterization for stationary memoryless sources is not easily derived. In this paper, we give single-letter characterizations for stationary memoryless sources under two types of restrictions: one requires the output distribution of the encoder to be independent and identically distributed (i.i.d.) and the other requires it to be memoryless but not necessarily i.i.d. asymptotically. The characterizations indicate the relation among the amount of information leakage, the minimum cost for information erasure and the rate of the size of uniformly distributed sequences. The obtained results show that the minimum costs are different between these restrictions.

Kurotto and Juosan are Nikoli's pencil puzzles. We study the computational complexity of Kurotto and Juosan puzzles. It is shown that deciding whether a given instance of each puzzle has a solution is NP-complete.

Wireless sensor and actuator networks (WSANs) are expected to become key technologies supporting machine-to-machine (M2M) communication in the Internet of things (IoT) era. However, sensors must be able to provide high demand response (DR) levels despite severely limited battery power. Therefore, as part of efforts to achieve a high DR, we are working on research and development related to radio-on-demand sensor and actuator networks (ROD-SANs). ROD-SAN nodes are equipped with wake-up receivers that allow all nodes to stay in sleep mode for a long period of time, and transmit only after the receiver receives a wake-up signal. In addition, sender nodes can direct the receiver nodes to switch communication channels because the wake-up signal also includes information on the channel to use for communication between each other. However, as the number of nodes utilizing the same channel increases, frequent packet collisions occur, thereby degrading response performance. To reduce packet collisions, we propose an own-channel-utilization based channel switching (OCS) scheme, which is a modification of the average-channel-utilization based switching (ACS) as our previous works. The OCS scheme decides whether or not to switch channels based on a probability value that considers not only average-channel utilization of nearby nodes but also own-channel utilization. This approach permits node switching to other channels by considering the overall utilization states of all channels. In this paper, based on simulations, we show that our scheme can improve the delivery ratio by approximately 15% rather than ACS scheme.

Finely textured structures on a silicon surface were fabricated to act as field emitters via simple sandblasting using fine Al2O3 particles. Tests confirmed that the finely nicked structures function well as efficient field emitters. The emission current obeys the Fowler-Nordheim relationship, with a low electric field threshold. The fluctuation of the emission current was inversely proportional to the square root of the average emission current, and the long-term drift of the emission current was about 1% per hour at the average emission current of 108µA in the pressure range of 10-5Pa, indicating that the emitter offers a stable current output.

Analyzing a malware sample requires much more time and cost than creating it. To understand the behavior of a given malware sample, security analysts often make use of API call logs collected by the dynamic malware analysis tools such as a sandbox. As the amount of the log generated for a malware sample could become tremendously large, inspecting the log requires a time-consuming effort. Meanwhile, antivirus vendors usually publish malware analysis reports (vendor reports) on their websites. These malware analysis reports are the results of careful analysis done by security experts. The problem is that even though there are such analyzed examples for malware samples, associating the vendor reports with the sandbox logs is difficult. This makes security analysts not able to retrieve useful information described in vendor reports. To address this issue, we developed a system called AMAR-Generator that aims to automate the generation of malware analysis reports based on sandbox logs by making use of existing vendor reports. Aiming at a convenient assistant tool for security analysts, our system employs techniques including template matching, API behavior mapping, and malicious behavior database to produce concise human-readable reports that describe the malicious behaviors of malware programs. Through the performance evaluation, we first demonstrate that AMAR-Generator can generate human-readable reports that can be used by a security analyst as the first step of the malware analysis. We also demonstrate that AMAR-Generator can identify the malicious behaviors that are conducted by malware from the sandbox logs; the detection rates are up to 96.74%, 100%, and 74.87% on the sandbox logs collected in 2013, 2014, and 2015, respectively. We also present that it can detect malicious behaviors from unknown types of sandbox logs.

Malicious software (malware) poses various significant challenges. One is the need to retrieve plain-text messages transmitted between malware and herders through an encrypted network channel. Those messages (e.g., commands for malware) can be a useful hint to reveal their malicious activities. However, the retrieving is challenging even if the malware is executed on an analysis computer. To assist analysts in retrieving the plain-text from the memory, this paper presents FCReducer(Function Candidate Reducer), which provides a small candidate set of cryptographic functions called by malware. Given this set, an analyst checks candidates to locate cryptographic functions. If the decryption function is found, she then obtains its output as the plain-text. Although existing systems such as CipherXRay have been proposed to locate cryptographic functions, they heavily rely on fine-grained dynamic taint analysis (DTA). This makes them weak against under-tainting, which means failure of tracking data propagation. To overcome under-tainting, FCReducer conducts coarse-grained DTA and generates a typical data dependency graph of functions in which the root function accesses an encrypted message. This does not require fine-grained DTA. FCReducer then applies a community detection method such as InfoMap to the graph for detecting a community of functions that plays a role in decryption or encryption. The functions in this community are provided as candidates. With experiments using 12 samples including four malware specimens, we confirmed that FCReducer reduced, for example, 4830 functions called by Zeus malware to 0.87% as candidates. We also propose a heuristic to reduce candidates more greatly.

When synthesizing speech from Japanese text, correct assignment of accent nuclei for input text with arbitrary contents is indispensable in obtaining naturally-sounding synthetic speech. A phenomenon called accent sandhi occurs in utterances of Japanese; when a word is uttered in a sentence, its accent nucleus may change depending on the contexts of preceding/succeeding words. This paper describes a statistical method for automatically predicting the accent nucleus changes due to accent sandhi. First, as the basis of the research, a database of Japanese text was constructed with labels of accent phrase boundaries and accent nucleus positions when uttered in sentences. A single native speaker of Tokyo dialect Japanese annotated all the labels for 6,344 Japanese sentences. Then, using this database, a conditional-random-field-based method was developed using this database to predict accent phrase boundaries and accent nuclei. The proposed method predicted accent nucleus positions for accent phrases with 94.66% accuracy, clearly surpassing the 87.48% accuracy obtained using our rule-based method. A listening experiment was also conducted on synthetic speech obtained using the proposed method and that obtained using the rule-based method. The results show that our method significantly improved the naturalness of synthetic speech.

Load size for a service on the Internet changes remarkably every hour. Thus, it is expected for service system scales to change dynamically according to load size. KVS (key-value store) is a scalable DBMS (database management system) widely used in largescale Internet services. In this paper, we focus on Cassandra, a popular open-source KVS implementation, and discuss methods for improving dynamic scaling performance. First, we evaluate node joining time, which is the time to complete adding a node to a running KVS system, and show that its bottleneck process is disk I/O. Second, we analyze disk accesses in the nodes and indicate that some heavily accessed files cause a large number of disk accesses. Third, we propose two methods for improving elasticity, which means decreasing node adding and removing time, of Cassandra. One method reduces disk accesses significantly by keeping the heavily accessed file in the page cache. The other method optimizes I/O scheduler behavior. Lastly, we evaluate elasticity of our methods. Our experimental results demonstrate that the methods can improve the scaling-up and scaling-down performance of Cassandra.

Network servers and applications commonly use static IP addresses and communication ports, making themselves easy targets for network reconnaissances and attacks. Moving target defense (MTD) is an innovatory and promising proactive defense technique. In this paper, we develop a novel MTD mechanism, called Random Port and Address Hopping (RPAH). The goal of RPAH is to hide network servers and applications and resist network reconnaissances and attacks by constantly changing their IP addresses and ports. In order to enhance the unpredictability, RPAH integrates source identity, service identity and temporal parameter in the hopping to provide three hopping frequencies, i.e., source hopping, service hopping and temporal hopping. RPAH provides high unpredictability and the maximum hopping diversities by introducing port and address demultiplexing mechanism, and provides a convenient attack detection mechanism with which the messages from attackers using invalid or inactive addresses/ports will be conveniently detected and denied. Our experiments and evaluation on campus network and PlanetLab show that RPAH is effective in resisting various network reconnaissance and attack models such as network scanning and worm propagation, while introducing an acceptable operation overhead.

Sharing data might bring the risk of disclosing the sensitive knowledge in it. Usually, the data owner may choose to sanitize data by modifying some items in it to hide sensitive knowledge prior to sharing. This paper focuses on protecting sensitive knowledge in the form of frequent itemsets by data sanitization. The sanitization process may result in side effects, i.e., the data distortion and the damage to the non-sensitive frequent itemsets. How to minimize these side effects is a challenging problem faced by the research community. Actually, there is a trade-off when trying to minimize both side effects simultaneously. In view of this, we propose a data sanitization method based on evolutionary multi-objective optimization (EMO). This method can hide specified sensitive itemsets completely while minimizing the accompanying side effects. Experiments on real datasets show that the proposed approach is very effective in performing the hiding task with fewer damage to the original data and non-sensitive knowledge.

We investigated client honeypots for detecting and circumstantially analyzing drive-by download attacks. A client honeypot requires both improved inspection performance and in-depth analysis for inspecting and discovering malicious websites. However, OS overhead in recent client honeypot operation cannot be ignored when improving honeypot multiplication performance. We propose a client honeypot system that is a combination of multi-OS and multi-process honeypot approaches, and we implemented this system to evaluate its performance. The process sandbox mechanism, a security measure for our multi-process approach, provides a virtually isolated environment for each web browser. It prevents system alteration from a compromised browser process by I/O redirection of file/registry access. To solve the inconsistency problem of file/registry view by I/O redirection, our process sandbox mechanism enables the web browser and corresponding plug-ins to share a virtual system view. Therefore, it enables multiple processes to be run simultaneously without interference behavior of processes on a single OS. In a field trial, we confirmed that the use of our multi-process approach was three or more times faster than that of a single process, and our multi-OS approach linearly improved system performance according to the number of honeypot instances. In addition, our long-term investigation indicated that 72.3% of exploitations target browser-helper processes. If a honeypot restricts all process creation events, it cannot identify an exploitation targeting a browser-helper process. In contrast, our process sandbox mechanism permits the creation of browser-helper processes, so it can identify these types of exploitations without resulting in false negatives. Thus, our proposed system with these multiplication approaches improves performance efficiency and enables in-depth analysis on high interaction systems.

This paper presents key recovery attacks on Sandwich-MAC instantiating MD5, where Sandwich-MAC is an improved variant of HMAC and achieves the same provable security level and better performance especially for short messages. The increased interest in lightweight cryptography motivates us to analyze such a MAC scheme. Our attacks are based on a distinguishing-H attack on HMAC-MD5 proposed by Wang et al. We first improve its complexity from 297 to 289.04. With this improvement, we then propose key recovery attacks on Sandwich-MAC-MD5 by combining various techniques such as distinguishing-H for HMAC-MD5, IV Bridge for APOP, dBB-near-collisions for related-key NMAC-MD5, meet-in-the-middle attack etc. In particular, we generalize a previous key-recovery technique as a new tool exploiting a conditional key-dependent distribution. Surprisingly, a key which is even longer than the tag size can be recovered without the knowledge of the key size. Finally, our attack also improves the previous partial-key (K1) recovery on MD5-MAC, and extends it to recover both of K1 and K2.

The noise in digital images acquired by image sensors has complex characteristics due to the variety of noise sources. However, most noise reduction methods assume that an image has additive white Gaussian noise (AWGN) with a constant standard deviation, and thus such methods are not effective for use with image signal processors (ISPs). To efficiently reduce the noise in an ISP, we estimate a unified noise model for an image sensor that can handle shot noise, dark-current noise, and fixed-pattern noise (FPN) together, and then we adaptively reduce the image noise using an adaptive Smallest Univalue Segment Assimilating Nucleus ( SUSAN ) filter based on the unified noise model. Since our noise model is affected only by image sensor gain, the parameters for our noise model do not need to be re-configured depending on the contents of image. Therefore, the proposed noise model is suitable for use in an ISP. Our experimental results indicate that the proposed method reduces image sensor noise efficiently.

In large-scale data centers, two types of network are implemented: local area networks (LANs) and storage area networks (SANs). To achieve simple network management, integration of these two networks by Ethernet technology is of great interest. A SAN requires a significantly low frame loss rate. To integrate LANs and SANs, a multi-hop Ethernet configuration is generally used, and congestion may occur in traffic hot spots. Therefore, layer-2 congestion control that prevents frame loss in multi-hop Ethernet, Quantized Congestion Notification (QCN), is now discussed in IEEE 802.1Qau. In this paper, we evaluate QCN's throughput performance and reveal a technical problem with fairness among active flows. We also propose Adaptive BC_LIMIT for QCN where BC_LIMIT is adaptively decided according to current transmission rate of flows. Simulation results show that our proposed method significantly improves fairness among QCN flows.

To realize economical optical burst signal receivers for the Optical Network Unit (ONU) of the Ethernet Optical Switched Access Network (E-OSAN), we previously implemented optical burst receivers with AC-coupling and DC-coupling using off-the-shelf components, and showed that the former offers better performance. This paper proposes a new optical burst signal receiver that uses the transfer function, Gn(s) = 1-Hn(s), where Hn(s) denotes a Bessel filter transfer function of order n. We also present a method for designing the proposed receiver and clarify that it has better performance than the conventional AC-coupling one. We then present an LCR circuit synthesis of Gn(s), which is necessary to actually implement a burst receiver based on the proposal.

A sanitizable signature scheme allows a semi-trusted party, designated by a signer, to modify pre-determined parts of a signed message without interacting with the original signer. To date, many sanitizable signature schemes have been proposed based on various cryptographic techniques. However, previous works are usually built upon the paradigm of dividing a message into submessages and applying a cryptographic primitive to each submessage. This methodology entails the computation time (and often signature length) in linear proportion to the number of sanitizable submessages. We present a new approach to constructing sanitizable signatures with constant overhead for signing and verification, irrespective of the number of submessages, both in computational cost and in signature size.

A sanitizable signature scheme is a signature scheme which, after the signer generates a valid signature of a message, allows a specific entity (sanitizer) to modify the message for hiding several parts. Existing sanitizable signature schemes require the message to be divided into pre-defined blocks before signing so that each block can be sanitized independently. However, there are cases where the parts of the message which are needed to be sanitized can not be determined in the time of signing. Thus, it is difficult to decide the partition of the blocks in such cases. Since the length of the signature is usually proportional to the number of blocks, signing every bit independently will make the signature too long. In this paper, we propose a solution by introducing a new concept called sequential bitwise sanitizable signature schemes, where any sequence of bits of the signed document can be made sanitizable without pre-defining them, and without increasing the length of signature. We also show that a one-way permutation suffices to get a secure construction, which is theoretically interesting in its own right, since all the other existing schemes are constructed using stronger assumptions.

The programming characteristics of polysilicon-aluminum oxide-nitride-oxide-silicon (SANOS) nonvolatile memory devices with Al2O3 and SiO2 stacked tunneling layers were investigated. The electron and hole drifts in the Si3N4 layer were calculated to determine the program speed of the proposed SANOS devices. Simulation results showed that enhancement of the programming speed in SANOS was achieved by utilizing SiO2 and Al2O3 stacked tunneling layers.

An Optical Line Terminal (OLT) needs to find and register newly connected Optical Network Units (ONUs) in the proposed Ethernet Optical Switched Access Network (E-OSAN) as well as the Ethernet Passive Optical Network (E-PON). In this discovery process, OLT measures round trip time (RTT) between OLT and each ONU and then assigns a Logical Link Identification (LLID) to each ONU. For E-OSAN, the conventional discovery method takes up to N discovery periods for OLT to register all ONUs, where N denotes the number of switch ports of the Optical Switching Module (OSM). This paper proposes an efficient method that completes discovery in just one period. This paper also evaluates the maximum ranging completion time of the proposed discovery method in a comparison with E-PON.